Casas Sergio, Coma Inmaculada, Riera José Vicente, Fernández Marcos
Hum Factors. 2015 Feb;57(1):144-62. doi: 10.1177/0018720814538281.
The aim of this study was to characterize the human response to motion-cuing algorithms (MCAs) by comparing users' perception to several proposed objective indicators.
Other researchers have proposed several MCAs, but few improvements have been achieved lately. One of the reasons for this lack of progress is that fair comparisons between different algorithms are hard to achieve, for their evaluation needs to be performed with humans and the tuning process is slow.
This characterization is performed by means of a comparison of the subjective perception of vehicle simulation users (90 participants) against several proposed objective indicators that try to measure MCA performance. Two motion platforms (3 and 6 degrees of freedom [DoF]) and two vehicle simulators (a driving simulator and a speedboat simulator) were tested using the classical washout algorithm, considered to be the main reference in MCA literature.
Results show that users are more sensitive to correlation and delay with respect to the expected motion rather than its magnitude and that specific force is more of a factor than angular speed in the driving simulator. The opposite happens in the speedboat simulator.
Human drivers' reaction to MCA is mainly characterized by the normalized Pearson correlation between output and input signals of the algorithm. This finding validates the main MCA strategy that consists of downscaling the signals and slightly distorting their frequency spectrum. The 6-DoF simulator is perceived as a modest improvement of the 3-DoF platform.
These results set the basis for future automatic tuning, evaluation, and comparison of MCA in motion platforms.
本研究旨在通过比较用户对几种提出的客观指标的感知，来表征人类对运动提示算法（MCA）的反应。
其他研究人员提出了几种MCA，但最近进展甚微。进展不足的原因之一是不同算法之间难以进行公平比较，因为它们的评估需要由人类进行，且调整过程缓慢。
通过将车辆模拟用户（90名参与者）的主观感知与几种试图测量MCA性能的提出的客观指标进行比较来进行这种表征。使用经典的洗出算法对两个运动平台（3和6自由度[DoF]）和两个车辆模拟器（驾驶模拟器和快艇模拟器）进行了测试，经典洗出算法被认为是MCA文献中的主要参考。
结果表明，用户对与预期运动的相关性和延迟比对其幅度更敏感，并且在驾驶模拟器中，比角速度更重要的因素是比力。在快艇模拟器中情况则相反。
人类驾驶员对MCA的反应主要由算法输出和输入信号之间的归一化皮尔逊相关性来表征。这一发现验证了主要的MCA策略，即对信号进行降尺度处理并轻微扭曲其频谱。6自由度模拟器被认为是3自由度平台的适度改进。
这些结果为未来运动平台中MCA的自动调整、评估和比较奠定了基础。
